Research On Asynchronous Diversity And Channel Estimation In Wireless Cooperative Relay Systems

Cooperative diversity system works by sharing antennas to form the virtual MIMO system. Cooperative diversity, which makes it possible that multi-antenna technology become practical application and has become an important means of transmission improve future wireless network performance. However, the distribution and mobility of cooperative antenna determines the existing research results cannot be directly applied to the cooperative system, which differ from the conventional MIMO systems. Therefore, this new issue of the new feature brought as the main research content for cooperative relay system.Numbers of key issues were discussed in this paper, with the cooperative technology as the research background. Mainly for the following aspects:First, due to the different distances result in different transmission propagation delay, when multiple relay to jointly transponder signal, seriously affect the performance of cooperative diversity system. However, most research is on the assumption that the conditions are too idealistic, such as the signals arrive simultaneously and has the precise time. Second, the current research on the channel estimate assumptions not existing frequency and time bias or considered separately. Most research on blind estimation is based on the assumption that channel has an ideal quasi-static or slow fading, what’s more, many issues need further research, such as computing capacity and inherent blurring.Most study about the cooperative diversity assumes that the system is ideally synchronized, which is far from the actual systems. Researches on diversity reception of asynchronous signal for cooperative relay system are summarized below:(1) Differ from the traditional processing method, using rather than preventing the asynchronous signal in this paper. The improved method of solving multiple access collision is applied to the system of cooperative relay system. Realize the reception of asynchronous signal diversity, using the forward and backward delete interference mechanism respectively for the cooperative relay system. It is proved that the system greatly reduces the complexity and can obtain the full diversity gain. On this basis, the performance of system can be further improved by increasing the error correcting code; finally, put feedback mechanism into the cooperative relay system, solved the poor performance of the system with the small delay for the proposed mechanism.(2) The blind receiver based on tensor models also proposed for the issue of the asynchronous signal in the cooperative relay system. Reconstruct the multiple asynchronous signals individually using the Parallel Factor Analysis decomposition. The analysis shows that it can still obtain better performance and a diversity gain in the absence of the system timing synchronization and the orthogonal channels. Finally, making the system performance and the convergence speed are further improved by optimizing the initialization of Alternating Least Squares.About channel estimation for the cooperative relay system, the main contents are summarized as follows:(1) To solve the problem of multiple carrier frequency offset and multiple timing offsets, we propose a channel estimation algorithm based on tensor model. The estimate and correct of frequency offset at the relay and terminal. Since the frequency offset correction, the good performance of system is still get by the TENCE in the presence of frequency offset. Finally, the estimation accuracy and system performance can be further improved by iterative.(2) The tracking algorithms are proposed based on the blind estimate for the cooperative system using the tensor model. Tracking the channel parameters using real-time adaptive PARAFAC decomposition, and to improve the performance by adjusting error parameter based on the two criteria of the least mean square and recursive least squares. Simulation results show that, compared with the traditional batch processing algorithm, the proposed tracking algorithms convergence is faster and complexity is lower. The proposed method is not only computed simply and flexibility to select the system parameters, compared with the matrix algorithm, but also solves the inherent ambiguity of blind estimation.This paper will seek a breakthrough in the field of cooperative diversity. The mechanism is challenging for solving problem of asynchronous diversity for cooperative system based on existing research. It is very practical to propose a better blind estimation method, when considering the frequency offset and instead the ideal channel estimation, by analyzing the existing channel estimation method.